/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

/*!
 * \file np_uniform_op.cc
 * \brief Implementation of the API of functions in src/operator/numpy/random/np_uniform_op.cc
 */
#include <mxnet/api_registry.h>
#include <mxnet/runtime/packed_func.h>
#include <vector>
#include "../utils.h"
#include "../../../operator/numpy/random/np_uniform_op.h"

namespace mxnet {

MXNET_REGISTER_API("_npi.uniform")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      const nnvm::Op* op = Op::Get("_npi_uniform");
      nnvm::NodeAttrs attrs;
      op::NumpyUniformParam param = {};
      int num_inputs = 0;
      std::vector<NDArray*> inputs;
      if (args[0].type_code() == kDLFloat || args[0].type_code() == kDLInt) {
        if (args[1].type_code() == kDLFloat || args[1].type_code() == kDLInt) {
          // 'low' and 'high' are both numeric types
          num_inputs = 0;
          param.low  = args[0].operator double();
          param.high = args[1].operator double();
        } else {
          // 'low' is numeric types but 'high' is not numeric types
          num_inputs = 1;
          param.low  = args[0].operator double();
          param.high = dmlc::nullopt;
        }
      } else {
        if (args[1].type_code() == kDLFloat || args[1].type_code() == kDLInt) {
          // 'low' is not numeric types but 'high' is numeric types
          num_inputs = 1;
          param.low  = dmlc::nullopt;
          param.high = args[1].operator double();
        } else {
          // nither 'low' or 'high' is numeric types
          num_inputs = 2;
        }
      }
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }
      if (args[2].type_code() == kNull) {
        param.size = dmlc::optional<mxnet::Tuple<index_t>>();
      } else if (args[2].type_code() == kDLInt || args[2].type_code() == kDLFloat) {
        param.size = Tuple<index_t>(1, args[2].operator int64_t());
      } else {
        param.size = Tuple<index_t>(args[2].operator ObjectRef());
      }
      if (args[4].type_code() == kNull) {
        param.dtype = mxnet::common::GetDefaultDtype();
      } else {
        param.dtype = String2MXNetTypeWithBool(args[4].operator std::string());
      }
      attrs.parsed = param;
      attrs.op     = op;
      if (args[3].type_code() != kNull) {
        attrs.dict["ctx"] = args[3].operator std::string();
      }
      NDArray* out      = args[5].operator mxnet::NDArray*();
      NDArray** outputs = out == nullptr ? nullptr : &out;
      int num_outputs   = out != nullptr;
      SetAttrDict<op::NumpyUniformParam>(&attrs);
      auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, outputs);
      if (out) {
        *ret = PythonArg(5);
      } else {
        *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
      }
    });

}  // namespace mxnet
